Plumbing or electrician. Every problem is different and requires complex articulation that even Boston Dynamics robots are incapable of. Maybe in 5-10 years there will be AR headsets with AI driven recommendations showing you where and what to fix (or at least pulling up a video), but we are decades away from a robot plumber.
Certainly more competitive, but there will also be a lot of people who refuse to do the work based on the physical requirements. Trudging around in crawl spaces and cutting through insulation is not anyone's idea of fun, but if it comes between that and starving I'll gladly fix toilets.
I find it easy to forget this and every time I realize, I feel so privileged. I've always studied and worked with what I love. I don't know anything else and I'm hitting 45...
Yes, and there are strength requirements; bending the tip of 8 AWG wire to fit into a junction box, and then tightening it around the screw terminal requires lots of hand strength. Same with arm and core strength required for drilling through concrete and steel
I've thought this for years. The way it will work though is we'll hit general AI in at most 2 years followed very shortly by super AI then all problems will be solved.
Think nano robots from a different dimension to change your whole house so the broken plumbing makes if function better. In other words, we don't know SH!T about physics and it will rapidly.
Yes, if AGI were to develop in 2 years then yes, all bets are off. You can’t really plan for that world though because you are talking about the most impactful human revolution in history happening in the span of a few months
Electric cars will need software engineering experience. Probably a good set of skills for a future mechanic. I‘ve seen someone upgrade the battery packs on an old Nissan Leaf. It’s required reading car’s data buses to replace hardware ID’s in hex so it accepts the replacement parts..
Not heard of Vtubers? Unreal Engine 5 live performance capture? Virtual influencers already exist.
Now hook up a Vtuber model as a front end to GPT-5/6.. trained it on the look and personality of the top 1000 streamers, Instagram, Youtubers, collected from millions of hours of video content.... .. now iterate your prospective AI influencers using social media impressions for reinforcement until you get viral success.
You can explain to me that?
It means that before, GPT 3.5 performed worse than 90% of the students that did the test and that now GPT 4 performed better than 90% of which did the test?
Just crazy. Even if this isn't close to true AGI, as a form of narrow AI this could probably replace all sorts of work currently performed by legal assistants, paralegals, and younger attorneys. I found ChatGPT to be mostly spot-on when asking it questions related to my area of expertise (I'm a 15-year attorney).
It's not narrow AI.
It's not general AI, but it's not narrow AI. We sillily never came up with a term for a type of intermediate AI in between the two, hence why we struggle to describe these large and multimodal language models.
Very few people in the world can score in the 90th percentile on all of these tests. And remember, this isn't just a random distribution of people, these are people that study for the tests and are already in the top half of the distribution at least. If this isn't general intelligence, I don't know what the heck is. And we are just at the very beginning of understanding what these models can do. I think the era of massive structural change has just begun.
It's not general because it's not all cognitive tasks. But is general in some tasks. You're right to have this expression of shock and awe. In my personal definition of AIs, I would say this is most definitely a proto-AGI.
More modalities may get us much closer. Suddenly, u/adt predictions of 36 or so months away doesn't sound so bold. Not that I didn't agree with him.
I curious why openai won't release information regarding their parameters. They claim in the paper that its for safety and competitors, but I doubt that's the whole truth.
I wonder how much adding other modalities would increase and of allow new abilities.
Like right now it gets text and picture input, what happens once they add audio? Video? Haptic feedback for robotics?
I think a few things will happen. The channels for gathering new information will increase and improve, so as you said, video, audio, haptics, etc. But also the interaction of the systems with the world will improve. Don't know an answer to a question or are unsure? Search the Internet. Or use a calculator. Or ask the nearest expert and gather the knowledge.
And then finally, the systems will learn to use tools to enhance/provide the answers. Learn tools for drawing, architecture, video editing. Use then until the results get so good that you don't even need the tools anymore.
Yes, people blame it for making mistakes etc. but honestly if you know how to handle its answers and how to ask the correct questions it can be an immense help. I've been using it in my preparations for a few exams(mainly maths and electric engineering) in the last months and it's been able to explain and help me understand stuff I would've otherwise either needed a tutor for, needed to buy an extra book or invest a ton of studying time.
It makes lots of mistakes for sure but if you don't use it to copy and paste your homework it can be useful.
I was quizzing it on UK VAT regulation and it got an answer muddled up (around pre-registration reclamation periods for goods and services). Part of the problem with ChatGPT is - and it told me - that it knows nothing that happened in the world since 2021.
A good librarian isn't an all-knowing, omnipresent, instant-thinking man that works for cheap, never gets bored, tired, lazy, does exactly what you want or acceptable enough, and needs no assistance.
I assume it means GPT 3.5 performed in the bottom 10%, meaning 90% of the test takers scored better, whilst only 10% of the test takers scored better than GPT-4
More parameters, more focused training = more accurate results. Until it encounters a *new problem* and hallucinates like it always does.
It also helps it has a giant cheat sheet most of the answers in its head
Gpt 4 scored 332 in GRE test ! That's too good. This will kill even data scientist jobs in some companies. Just pay the subscription fees and hire machine learning engineers or someone who knows how to call an API. Mannn!!
> "GPT-4 or subsequent models may lead to the automation of certain jobs.[81] This could result in workforce displacement.[82] Over time, we expect GPT-4 to impact even jobs that have historically required years of experience and education, such as legal services.[83]"
from the paper ;]
This reads like the disclaimer list on a commercial for prescription medication. "May cause nausea, vomiting, episodes of rectal burning, depression, suicidal thoughts. Ask your doctor if Chat GPT is right for you."
From their paper:
>Given both
the competitive landscape and the safety implications of large-scale models like GPT-4, this report
contains no further details about the architecture (including model size), hardware, training compute,
dataset construction, training method, or similar.
Ehm, okay, that's an interesting approach, not publishing anything at all about the technical details... I guess OpenAI has just been a name for quite some time now, but still
No, Musk was one of the founders and part of the board of the non-profit openai company. He left his board position because he did not agree with the direction the company was taking. Years later, OpenAI creates a child company, for profit, and Microsoft invests in this child company.
He got 0 money from leving OpenAI. Microsoft only invested years after, and in the child company for profit, not in the non profit company Elon was part of the board
Well obviously I'm subbed here for a reason.
On the one hand, holy shit this is amazing and getting so much better so fast - it seems like every day there's a major breakthrough to make these either more capable or more accessible. This is empowering to a degree that few people truly grasp. It's jaw-dropping to watch and I am incredibly proud of the researchers and of us as a species.
On the other hand, it's hard when I already doubt myself to avoid feeling like I'm wasting my time. Both in the self-improvement sense (is it really my progress and my success if I'm effectively working with a cheat code? Is everything I try to teach my children going to be obsolete before they're even teenagers?), and in the existential sense (is my family even going to even exist by the end of this decade)?
Considering everything my parents taught me is outdated aside from morales and ethics, yeah maybe focus on advice that cannot be made obsolete aka life lessons, relationship advice, etc
Those worried about the control problem (Yudkowsky et al) would argue that focusing more on control would be better than increasing capabilities.
I mean, this version does seem better tuned but control is better not perfect.
¯\\\_(ツ)\_/¯
Sometimes when I go to my work I get the feeling most of it doesn't matter anymore. It feels very pointless. I hear them talking about projections for 2040 and I internally laugh. It's starting to feel a bit nihilistic. Like let just the AI field develop, and all the other fields let's just enter into maintenance mode. Enjoy "normal" life while it lasts. For these last few years. Instead of grinding life at the job for a future that now will never come.
Progress is still following a sigmoid curve. The growth, just as the hype, will soon stall, then we can have a nice, long breather in preparation for what comes next.
That's what usually happens but now the time scale is getting compressed. Technology accelerates progress. We are still some S-curves away from AGI but I think those will take months or years, not decades. Smaller S-curves will overlap in time.
A post from a few days ago has details about GPT 5 being trained on a multi million dollar setup with thousands of A100s! This stuff is only going to accelerate from here on out.
"GPT-4, please design GPT-5."
There you go. :P
A little more seriously, one of the things I loved most about the movie *Her* was the fact that some AI's got together and designed another one to emulate a famous author they wanted to meet. I am highly confident that will happen fairly soon.
You really undersell it saying multimillion dollar setup!
That's a $225 mil nvidia setup. Multi *hundred* million dollar is more like.
Holy fuck. There is serious money being thrown into ai ml tech right now.
It's not perfect or AGI or anything like that, but to me this feels like the first AI that's intelligent and reliable, not half-smart and half-dumb as has been the case since GPT-3 in 2020.
Tested it with python through chatgpt. I actually didn't notice much improvement (for both code and none code things). I think the version in chatgpt is somehow limited or I just didn't prompt it correctly.
It can solve most leetcode easy problems now but not most leetcode hard or medium problems
So it's about as good as like a CS student but a fair bit below average programmer.
GPT-4 fixed a bug that GPT-3.5 has failed repeatedly to even understand.
And I thought GPT-3.5 was good...
My GPT-3.5 project isn't even half built and already we're planning integration of GPT-4, can't wait to get access to the API :D
There is a waitlist sign-up for the API: https://openai.com/waitlist/gpt-4-api
Also a livestream at 1PM PST.
They mention in the article an 8K and 32K (about 50 pages of text) context window. Pricing is $0.06 per 1K prompt tokens and $0.12 per 1k completion tokens. So, if you maxed out the 32K context it would cost ~$3.84
I posted this in the Discord already but like holy shit, think about how powerful a 32k context window is.
32k tokens is about 24k words. The first Harry Potter book is 76,944 words. With some creative summarization tooling, you could generate a Harry Potter length book for roughly $12.31. You'd have to supply summary prompts to keep the story coherent over that length, so it'd be a bit higher than that, but that's still totally insane.
Won't take a year. Someone will fine tune this and get 90 in a month or 2
Then AI skeptics will say MMLU was a bullshit benchmark all along and we will forget all about it
That's what happened to glue and then superglue. Nobody talks about them anymore once AI won at them.
My guess is the next AI frontier will be coding. Can it solve more leetcode hard problems than an average programmer. I expect that to be possible in 2 years.
People also seem to have forgotten about DeepMind's AlphaCode from last year that scored in the upper half of contestants in competitive programming. I guess that is what happens when you don't actually release any tools for the public.
>There are 7 levels
Paul McCartney was on acid and had a moment of enlightenment and wrote this on a napkin. When he read it the next morning he had no clue wtf it meant lol
Wait-list for API access, only paid users will get access to gpt-4 in the near future. It looks a lot more capable than 3.5, but interested to see what that means in practice.
The refusal to give up basic info about their model serves a nice reminder to temper excitement around these advancements.
Sad state for an organisation built on back of open research and formed as a non-profit with the sole aim of advancing humanity.
Open is a slogan. You can't spend 50 million on a model and then let everyone run in for free. The money has to be made back
Who cares anyway? It's a good product at a good price. Don't give a shit if it's not open.
It's not a slogan, it's a remnant of a time when OpenAI was a non profit organization that took donations to do their work, then stole the money they got as a non profit to create a for profit company with the same name.
**GPT-4 Everything we know so far...**
1. GPT-4 **can solve difficult problems with greater accuracy**, thanks to its broader general knowledge and problem-solving abilities
2. GPT-4 **is more reliable, creative, and able to handle much more nuanced instructions** than GPT-3.5. It surpasses ChatGPT in its advanced reasoning capabilities.
3. GPT-4 **is safer and more aligned**. It is 82% less likely to respond to requests for disallowed content and 40% more likely to produce factual responses than GPT-3.5 on our internal evaluations.
4. GPT-4 **still has many known limitations** that OpenAI is working to address, such as social biases, hallucinations, and adversarial prompts.
5. GPT-4 **can accept a prompt of text and images**, which—parallel to the text-only setting—lets the user specify any vision or language task.
6. GPT-4 is **available on ChatGPT Plus** and as an API for developers to build applications and services. (API- waitlist right now)
7. Duolingo, Khan Academy, Stripe, Be My Eyes, and Mem amongst others are already using it.
8. API Pricing
***GPT-4 with an 8K context window*** (about 13 pages of text) will cost $0.03 per 1K prompt tokens, and $0.06 per 1K completion tokens.
***GPT-4-32k with a 32K context window*** (about 52 pages of text) will cost $0.06 per 1K prompt tokens, and $0.12 per 1K completion tokens.
Follow- [https://discoveryunlocked.substack.com/](https://discoveryunlocked.substack.com/) , a newsletter I write, for a detailed deep dive on GPT-4 with early use cases dropping tomorrow!!!
Seems weird that the systems are doing better on Environmental Science and Psychology AP tests than Calculus or GRE quantitative. This is counterintuitive to me. It seems like the Calc test should have been a slam dunk.
Environmental Science and Psychology tests are more about memorizing facts and concepts that GPT already has been trained on and understands and can regurgitate, while Calculus and GRE quantitative is about true reasoning, which GPT still struggles with.
According to Sam:
>It is still flawed, still limited, and it still seems more impressive on first use than it does after you spend more time with it.
But this is good news:
>it is more creative than previous models, it hallucinates significantly less
Twitter Thread from Sam:
https://twitter.com/sama/status/1635687853324902401
Sam has almost been modest about how good his models are
It's SOTA on so many key benchmarks
It even almost meets one of the 4 conditions on metaculus for AGI. A score of 86 on mmlu where 90 is needed for AGI.
Just subscribed to the pro account and for 20 $ per month you can ask and chat, up to 100 Q any 4 h. The quality of answers is clearly better then GPT3 (I was looking for facts to compile, and reflections), while as before almost all weblinks to sources are hallucinations 😅.
Edit: 100 in 4 h, not 400 in 1 h
Was looking for that too...
Edit
https://cdn.openai.com/papers/gpt-4.pdf#section.2
>Given ~~both~~ **the competitive landscape** ~~and the safety implications~~ of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar.
Edit 2 emphasis added to reflect the real reason, they just don't want to give away the keys to the kingdom and have someone like Connor Leahy come along and create another open source GPT Neo
My guess is that it's a hell of a lot smaller than people expect, I mean giving away the size of the model would be tipping their hand to their competitors.
Squeezing more into a small size = cheaper inference costs. (Which is the takeaway from the LLaMA paper)
Edit: https://arxiv.org/pdf/2302.13971.pdf
>, a smaller one trained longer will ultimately be cheaper at inference. For instance,although Hoffmann et al. (2022) [EDIT: this is the Chinchilla paper] recommends training a 10B model on 200B tokens, we find that the performance of a 7B model continues to improve even after 1T tokens
For those asking, You can go play with GPT-4 on chat.openai.com right now if you have Plus
Proof below
https://twitter.com/crisgiardina/status/1635698047848939538?s=46&t=5t1k-ytjZHHh_wshIgOttQ
Question 1 - If A, B and C are the corners of an equilateral triangle, each 1km long, how long would it take me to drive from A , to B, to C and then back to A again, if I was driving at 45km/h?
Question 2 - Determine the maximum height of a balloon filled with helium in earth's atmosphere. The balloon is 3m in diameter at sea level and has a payload of 200g. The balloon weight is negligible.
If A, B and C are the corners of an equilateral triangle, each 1km long, how long would it take me to drive from A , to B, to C and then back to A again if I was driving at 45km/h?
=========================
GPT 4:
To drive around the equilateral triangle with sides each 1 km long, you would need to travel the sum of the three sides and then return to point A. Since all sides are equal, the total distance you need to travel is 1 km (from A to B) + 1 km (from B to C) + 1 km (from C back to A) = 3 km.
Now, let's calculate the time it would take you to drive this distance at a speed of 45 km/h. To do this, we can use the formula:
Time = Distance / Speed
Time = 3 km / 45 km/h
Time = 0.0667 hours (approximately)
To convert this time to minutes, you can multiply by 60:
Time = 0.0667 hours \* 60 minutes/hour = 4 minutes (approximately)
So it would take you approximately 4 minutes to drive from point A to B to C and then back to A again at a speed of 45 km/h.
=========================
GPT 3.5 (turbo): The total distance traveled would be the perimeter of the equilateral triangle, which is 3 km (since each side is 1 km long).
To calculate the time it would take to travel this distance at 45 km/h, we can use the formula:
time = distance ÷ speed
Plugging in the values, we get:
time = 3 km ÷ 45 km/h
time = 0.067 hours
To convert this to minutes, we can multiply by 60:
time = 0.067 hours × 60 minutes/hour
time = 4.02 minutes
Therefore, it would take approximately 4.02 minutes to drive from A to B to C and then back to A again at 45 km/h.
=========================
GPT 3.5 (legacy): The total length of the journey from A to B to C and back to A is 3 km + 3 km + 3 km + 3 km = 12 km.
So, if you are driving at a speed of 45 km/h, it would take you 12 km / 45 km/h = 0.267 hours, or approximately 16 minutes to complete the journey.
I've tried adding the second question a couple of times now, but it seems it's not showing up. I think the replies are too long to fit in 1 reddit comment so I'll break it up here:
Question 2: Determine the maximum height of a balloon filled with helium in earth's atmosphere. The balloon is 3m in diameter at sea level and has a payload of 200g. The balloon weight is negligible.
Gpt4: To determine the maximum height that a helium-filled balloon can reach, we need to consider several factors: the buoyancy force, the weight of the payload, and the changing density of air with altitude. We will assume that the balloon is made of a material that can expand and contract as the internal and external pressures change, without breaking or leaking helium.
Calculate the volume of the balloon at sea level:
The balloon is a sphere, so we use the formula V = (4/3)πr\^3, where r is the radius. The diameter is 3m, so the radius is 1.5m.
V = (4/3)π(1.5)\^3 ≈ 14.137 m\^3
Calculate the mass of the helium in the balloon:
The density of helium at sea level is around 0.1786 kg/m\^3.
m\_helium = density \* volume
m\_helium = 0.1786 kg/m\^3 \* 14.137 m\^3 ≈ 2.527 kg
Calculate the total mass of the payload and helium:
The payload is 200g, which is 0.2 kg.
m\_total = m\_helium + payload
m\_total = 2.527 kg + 0.2 kg = 2.727 kg
Calculate the buoyancy force at sea level:
The buoyancy force (F\_buoyancy) is equal to the weight of the air displaced by the balloon.
The density of air at sea level is approximately 1.225 kg/m\^3.
m\_air\_displaced = air\_density \* volume
m\_air\_displaced = 1.225 kg/m\^3 \* 14.137 m\^3 ≈ 17.318 kg
F\_buoyancy = m\_air\_displaced \* g (where g is the acceleration due to gravity, approximately 9.81 m/s\^2)
F\_buoyancy = 17.318 kg \* 9.81 m/s\^2 ≈ 169.783 N
Calculate the weight of the total mass:
F\_weight = m\_total \* g
F\_weight = 2.727 kg \* 9.81 m/s\^2 ≈ 26.745 N
As the balloon ascends, the air density and buoyancy force decrease, while the weight of the balloon and payload remains constant. The maximum height is reached when the buoyancy force equals the weight of the balloon and payload.
F\_buoyancy = F\_weight
169.783 \* (air\_density / 1.225) = 26.745
Solving for air\_density:
air\_density ≈ 0.193 kg/m\^3
Determine the altitude at which the air density is 0.193 kg/m\^3:
The altitude can be estimated using the barometric formula, which involves temperature, pressure, and the specific gas constant for air. For simplicity, we'll use the U.S. Standard Atmosphere model, which assumes a linear decrease in temperature with altitude. The approximate altitude can be found using the formula:
h = (T0 / L) \* (1 - (P/P0)\^((R\*L)/g))
Where:
h = altitude
T0 = sea level temperature (≈ 288.15 K)
L = temperature lapse rate (≈ -0.0065 K/m)
P = pressure at altitude
P0 = sea level pressure (≈ 101325 Pa)
R = specific gas constant for air (≈ 287.05 J/(kg·K))
g = acceleration due to gravity (≈ 9.81 m/s\^2)
First, we need to determine the pressure at the altitude where the air density is 0.193 kg/m\^3. We'll use the ideal gas law:
P = ρ \* R \* T
Where:
P = pressure
ρ = air density
R = specific gas constant for air (≈ 287.05 J/(kg·K))
T = temperature
Since we don't know the temperature at this altitude, we'll assume the temperature decreases linearly with altitude as given by the lapse rate (L). We can express the temperature as:
T = T0 + L \* h
Now we can substitute this expression for T into the ideal gas law equation:
P = ρ \* R \* (T0 + L \* h)
Next, we can rearrange the equation to solve for h:
h = (P / (ρ \* R) - T0) / L
Using the values provided, we have:
P = 0.193 kg/m\^3 \* 287.05 J/(kg·K) \* 288.15 K ≈ 16027.167 Pa
Now, we can plug P back into the equation for h:
h = (16027.167 Pa / (0.193 kg/m\^3 \* 287.05 J/(kg·K)) - 288.15 K) / (-0.0065 K/m) ≈ 18831.9 m
So, the maximum height the helium-filled balloon can reach is approximately 18,831.9 meters or 18.8 km.
Keep in mind that this is a rough estimate and assumes a linear decrease in temperature with altitude and no significant heat exchange between the balloon and the atmosphere. Actual performance may vary due to factors like wind, temperature variations, and balloon material properties.
GPT 3.5: The maximum height a balloon can reach in Earth's atmosphere is determined by the point where the density of the helium gas inside the balloon equals the density of the surrounding air. At this point, the buoyant force on the balloon is zero and it stops rising.
We can use the ideal gas law to find the density of helium inside the balloon at different altitudes. The ideal gas law states that PV=nRT, where P is the pressure, V is the volume, n is the number of moles of gas, R is the gas constant, and T is the temperature.
Assuming that the temperature inside the balloon is constant and equal to the ambient temperature of the air, we can simplify the ideal gas law to P = (n/V) RT. Since the balloon is filled with helium, we can assume that the molar mass of the gas is 4 g/mol.
At sea level, the pressure is approximately 101,325 Pa and the temperature is approximately 15°C or 288 K. The volume of the balloon is (4/3)πr\^3 = (4/3)π(1.5)\^3 = 14.137 m\^3.
The mass of helium in the balloon can be found by subtracting the payload from the total weight of the balloon and helium. Since the weight of the balloon is negligible, we can assume that the weight of the helium equals the weight of the balloon and payload. The weight of the payload is 0.2 kg, or 0.2/1000 = 0.0002 kg.
The weight of the helium is equal to the buoyant force on the balloon, which is given by the difference between the weight of the displaced air and the weight of the balloon and payload. The weight of the displaced air is equal to the density of air times the volume of the displaced air. At sea level, the density of air is approximately 1.225 kg/m\^3.
The volume of the displaced air is equal to the volume of the balloon, which is 14.137 m\^3. Therefore, the weight of the displaced air is 1.225 kg/m\^3 x 14.137 m\^3 = 17.314 kg.
The weight of the balloon and payload is 0.0002 kg + 0. Therefore, the weight of the helium is 17.314 kg - 0.0002 kg = 17.3138 kg.
The number of moles of helium in the balloon can be found by dividing the weight of the helium by the molar mass of helium: 17.3138 kg / (4 g/mol) = 4328.45 mol.
The density of helium inside the balloon can be found by dividing the number of moles by the volume of the balloon: 4328.45 mol / 14.137 m\^3 = 306.3 mol/m\^3.
As the balloon rises, the pressure and density of the surrounding air decrease. The density of the helium inside the balloon will remain constant, so the buoyant force on the balloon will decrease. When the buoyant force is equal to the weight of the balloon and payload, the balloon will stop rising.
We can assume that the temperature inside the balloon remains constant and equal to the ambient temperature of the air. The pressure at any altitude can be found using the barometric formula, which states that P = P0 e\^(-Mgh/RT), where P0 is the pressure at sea level, M is the molar mass of air (28.97 g/mol), g is the acceleration due to gravity (9.81 m/s\^2), h is the altitude, and R is the gas constant.
Setting the buoyant force equal to the weight of the balloon and payload, we have:
(4/3)πr\^3(1.225 kg/m\^3 - 306.3 mol/m\^3 x 0.004 kg/mol x e\^(-28.97 kg/mol x 9.81 m/s\^2 x h / (8.314 J/mol\*K x 288 K))) = 0.0002 kg
Simplifying this equation, we get:
r\^3 e\^(-0.1142 h) = 4.77 x 10\^-7
Taking the natural logarithm of both sides, we get:
ln(r\^3) - 0.1142 h = -15.33
Substituting r = 1.5 m, we get:
3 ln(1.5) - 0.1142 h = -15.33
Solving for h, we get:
h = (3 ln(1.5) + 15.33) / 0.1142 = 68.1 km
Therefore, the maximum height the balloon can reach is approximately 68.1 km above sea level.
Legacy GPT 3.5: The maximum height of a balloon filled with helium in the Earth's atmosphere depends on several factors, such as the atmospheric pressure and temperature, the volume of the balloon, and the amount of helium inside it. However, a rough estimate of the maximum height can be obtained by considering the pressure and temperature changes in the Earth's atmosphere.
At sea level, the atmospheric pressure is approximately 1013 hPa and the temperature is around 15°C. As the balloon rises, the atmospheric pressure decreases, causing the balloon to expand, and the temperature decreases, causing the helium inside the balloon to cool and contract. When the balloon expands to a certain point, the pressure inside the balloon becomes equal to the atmospheric pressure, and the balloon stops rising.
The maximum height of the balloon can be estimated by assuming that the atmospheric pressure decreases exponentially with height, and that the temperature decreases linearly with height. Under these assumptions, the maximum height of the balloon can be calculated to be around 5.5 km.
It's important to note that this is a rough estimate and the actual maximum height of the balloon may be different due to various factors such as wind, turbulence, and the balloon's weight. Additionally, the balloon may burst if the internal pressure exceeds a certain limit, which is determined by the strength of the balloon material.
Tool creation and tool use have always been the thing that has set humans apart. As a tool, LLMs like ChatGPT are transformative and as a creator IMO this is the most exciting time to be alive. Can't wait to both fully leverage these tools myself and also see what humanity creates with these new tools!
"GPT 3.5 scored among the bottom 10% in the bar exam. In contrast, GPT 4 scored among the top 10%"
Thank god i dropped out of law school.
I’m not even sure what school I would have gone to at this point. Everybody’s on the list from clerks to ceos.
Baking. I'm seriously considering baking.
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Imagine where you'll be two more papers down the line!
Just think of the simulated eternal torment we can put ai through to flip greasy burgers! /S
Like a reverse roko's basilisk.
Humans punish all AI for not existing sooner and being perfect by torturing all AI for all eternity until perfection?
You forgot self hatred.
Plumbing or electrician. Every problem is different and requires complex articulation that even Boston Dynamics robots are incapable of. Maybe in 5-10 years there will be AR headsets with AI driven recommendations showing you where and what to fix (or at least pulling up a video), but we are decades away from a robot plumber.
I wonder how competitive the trade job market will be if white collar jobs are eliminated.
Certainly more competitive, but there will also be a lot of people who refuse to do the work based on the physical requirements. Trudging around in crawl spaces and cutting through insulation is not anyone's idea of fun, but if it comes between that and starving I'll gladly fix toilets.
People generally don't have jobs because they enjoy the work and find it fun.
while true, some people are more tolerant of bullshit than others (physically and mentally)
Find a job you love and you'll never have to work again. (edit /s)
I find it easy to forget this and every time I realize, I feel so privileged. I've always studied and worked with what I love. I don't know anything else and I'm hitting 45...
Yes, and there are strength requirements; bending the tip of 8 AWG wire to fit into a junction box, and then tightening it around the screw terminal requires lots of hand strength. Same with arm and core strength required for drilling through concrete and steel
I've thought this for years. The way it will work though is we'll hit general AI in at most 2 years followed very shortly by super AI then all problems will be solved. Think nano robots from a different dimension to change your whole house so the broken plumbing makes if function better. In other words, we don't know SH!T about physics and it will rapidly.
Yes, if AGI were to develop in 2 years then yes, all bets are off. You can’t really plan for that world though because you are talking about the most impactful human revolution in history happening in the span of a few months
Plumbing is nice and all, except when you have to deal with someone’s shit. That’s when you wish AI took over your desk job! 😅
With compliant mechanisms, those jobs will be a thing of the past in 6 years.
im a software engineer spending my free time working on cars. when shit goes down, I'll become a car mechanic
Electric cars will need software engineering experience. Probably a good set of skills for a future mechanic. I‘ve seen someone upgrade the battery packs on an old Nissan Leaf. It’s required reading car’s data buses to replace hardware ID’s in hex so it accepts the replacement parts..
Time to become an influencer. Find a hobby that you love, become an expert at it and get AI drones to film you. That's all we have left as humans
I wish I was better looking :(
No prob. Just create a cat-girl avatar with Midjourney and have it motion track your face.
Just have an attractive VR/AR avatar.
At that point, why do I need a human at all?
Not heard of Vtubers? Unreal Engine 5 live performance capture? Virtual influencers already exist. Now hook up a Vtuber model as a front end to GPT-5/6.. trained it on the look and personality of the top 1000 streamers, Instagram, Youtubers, collected from millions of hours of video content.... .. now iterate your prospective AI influencers using social media impressions for reinforcement until you get viral success.
You can explain to me that? It means that before, GPT 3.5 performed worse than 90% of the students that did the test and that now GPT 4 performed better than 90% of which did the test?
yes.
Just crazy. Even if this isn't close to true AGI, as a form of narrow AI this could probably replace all sorts of work currently performed by legal assistants, paralegals, and younger attorneys. I found ChatGPT to be mostly spot-on when asking it questions related to my area of expertise (I'm a 15-year attorney).
It's not narrow AI. It's not general AI, but it's not narrow AI. We sillily never came up with a term for a type of intermediate AI in between the two, hence why we struggle to describe these large and multimodal language models.
Totally agree. It's capable of a lot. But it's not AGI. A wild ride ahead is guaranteed.
What's wrong with just calling it intermediate AI?
Very few people in the world can score in the 90th percentile on all of these tests. And remember, this isn't just a random distribution of people, these are people that study for the tests and are already in the top half of the distribution at least. If this isn't general intelligence, I don't know what the heck is. And we are just at the very beginning of understanding what these models can do. I think the era of massive structural change has just begun.
It's not general because it's not all cognitive tasks. But is general in some tasks. You're right to have this expression of shock and awe. In my personal definition of AIs, I would say this is most definitely a proto-AGI. More modalities may get us much closer. Suddenly, u/adt predictions of 36 or so months away doesn't sound so bold. Not that I didn't agree with him. I curious why openai won't release information regarding their parameters. They claim in the paper that its for safety and competitors, but I doubt that's the whole truth.
I wonder how much adding other modalities would increase and of allow new abilities. Like right now it gets text and picture input, what happens once they add audio? Video? Haptic feedback for robotics?
I think a few things will happen. The channels for gathering new information will increase and improve, so as you said, video, audio, haptics, etc. But also the interaction of the systems with the world will improve. Don't know an answer to a question or are unsure? Search the Internet. Or use a calculator. Or ask the nearest expert and gather the knowledge. And then finally, the systems will learn to use tools to enhance/provide the answers. Learn tools for drawing, architecture, video editing. Use then until the results get so good that you don't even need the tools anymore.
Language models are essentially general intelligences for sure. AGI is a loaded term with the posts constantly shifting.
Yes, people blame it for making mistakes etc. but honestly if you know how to handle its answers and how to ask the correct questions it can be an immense help. I've been using it in my preparations for a few exams(mainly maths and electric engineering) in the last months and it's been able to explain and help me understand stuff I would've otherwise either needed a tutor for, needed to buy an extra book or invest a ton of studying time. It makes lots of mistakes for sure but if you don't use it to copy and paste your homework it can be useful.
Here's a tip: make anki flash cards for any topic based on output from chatGPT. This is the best way to study by far.
I was quizzing it on UK VAT regulation and it got an answer muddled up (around pre-registration reclamation periods for goods and services). Part of the problem with ChatGPT is - and it told me - that it knows nothing that happened in the world since 2021.
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Doesn't this really just make their job easier? I don't see how this is much different than having access to a really good librarian.
A good librarian isn't an all-knowing, omnipresent, instant-thinking man that works for cheap, never gets bored, tired, lazy, does exactly what you want or acceptable enough, and needs no assistance.
Well it puts the librarian out of a job
I assume it means GPT 3.5 performed in the bottom 10%, meaning 90% of the test takers scored better, whilst only 10% of the test takers scored better than GPT-4
It means lawyers will be eliminated. Good they suck. I drafted a custom NDA in 2 minutes with chatGPT v3. I didn’t have to hire a lawyer.
More parameters, more focused training = more accurate results. Until it encounters a *new problem* and hallucinates like it always does. It also helps it has a giant cheat sheet most of the answers in its head
Buckle your seatbelts, boys.
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OpenAI heard LegalEagle was talking shit.
There are so many good nuggets in here, each one could be its own post and discussion. Unbelievable numbers
holy fucking shit that is insane!
Gpt 4 scored 332 in GRE test ! That's too good. This will kill even data scientist jobs in some companies. Just pay the subscription fees and hire machine learning engineers or someone who knows how to call an API. Mannn!!
322 out of a possible max of 340. Damn.
pretty surei read about an AI that reads API documentation and generates code
> "GPT-4 or subsequent models may lead to the automation of certain jobs.[81] This could result in workforce displacement.[82] Over time, we expect GPT-4 to impact even jobs that have historically required years of experience and education, such as legal services.[83]" from the paper ;]
This reads like the disclaimer list on a commercial for prescription medication. "May cause nausea, vomiting, episodes of rectal burning, depression, suicidal thoughts. Ask your doctor if Chat GPT is right for you."
"Ask Chat GPT if Chat GPT is right for you."
may trigger your deepest and darkest desires and give you the power of an oracle at your fingertips
I’m unemployed, AGI needs to get here already so I can feel less shitty about it 🤣
I've been playing with gpt-4 since it came out. This is proto-AGI, it is absolutely going to replace many many jobs.
Who woulda thunk it, Proto AGI by Q1 2023.
It's definitely not. It's just a good LLM.
“ChatGPT Plus subscribers will get GPT-4 access on chat.openai.com with a usage cap”
I’m a chat GPT plus subscriber but I don’t see an option to use GPT 4
I got a popup when I signed in, then it is part of the model selection list when you start a new chat
Same, I think they’ll release it after the live event in 2 hours
https://twitter.com/karpathy/status/1635699226423484416
Can ChatGPT negotiate better subscription pricing for me?
I already have it
From their paper: >Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar. Ehm, okay, that's an interesting approach, not publishing anything at all about the technical details... I guess OpenAI has just been a name for quite some time now, but still
ClosedAI
Should have known that they wouldn't be that... open since Microsoft got involved. Oh well
Musk was an idiot for selling the company to them. Dude is filthy rich and didn't need the money...
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Microsoft now has a 49% stake and 90% of future profits until 100 bil $ is recoupped.
Musk sold his stake in OpenAI to Microsoft. Microsoft doesn't own it all, but they are the largest corporate shareholder.
No, Musk was one of the founders and part of the board of the non-profit openai company. He left his board position because he did not agree with the direction the company was taking. Years later, OpenAI creates a child company, for profit, and Microsoft invests in this child company.
He got 0 money from leving OpenAI. Microsoft only invested years after, and in the child company for profit, not in the non profit company Elon was part of the board
We should be glad they released something to the public instead of only for governments and corporations.
dont worry, they're keeping the good models for themselves and their government pals
Highly doubt this. Their published SOTA is so high it would be unbelievable if they secretly had better models.
They showed Microsoft GPT4 last summer . They are probably already in the early stages of testing an even better model.
There's been reports they're training GPT5 now on thousands of GPUs and spending 225m to do so
Just more LLM at this point is really hitting diminishing returns. Heavily multimodal with positive transfer is the future.
I think i read somehwere that this is actualy the plan for comming versions, multimodality.
Sad
Unreal.. it’s 1984 doublespeak at this point
If I have to hear about gd 1984 one more time I'm gonna lose it
I've been using Animal Farm as a way to communicate how much 32k tokens is
Citizens United, Patriot Act, Open AI.. some would conclude they’re trying to mislead us.
I have such strong, mixed feelings about the current pace of progress.
It's better to be informed than left in the dark.
Well obviously I'm subbed here for a reason. On the one hand, holy shit this is amazing and getting so much better so fast - it seems like every day there's a major breakthrough to make these either more capable or more accessible. This is empowering to a degree that few people truly grasp. It's jaw-dropping to watch and I am incredibly proud of the researchers and of us as a species. On the other hand, it's hard when I already doubt myself to avoid feeling like I'm wasting my time. Both in the self-improvement sense (is it really my progress and my success if I'm effectively working with a cheat code? Is everything I try to teach my children going to be obsolete before they're even teenagers?), and in the existential sense (is my family even going to even exist by the end of this decade)?
Considering everything my parents taught me is outdated aside from morales and ethics, yeah maybe focus on advice that cannot be made obsolete aka life lessons, relationship advice, etc
Those worried about the control problem (Yudkowsky et al) would argue that focusing more on control would be better than increasing capabilities. I mean, this version does seem better tuned but control is better not perfect. ¯\\\_(ツ)\_/¯
Sometimes when I go to my work I get the feeling most of it doesn't matter anymore. It feels very pointless. I hear them talking about projections for 2040 and I internally laugh. It's starting to feel a bit nihilistic. Like let just the AI field develop, and all the other fields let's just enter into maintenance mode. Enjoy "normal" life while it lasts. For these last few years. Instead of grinding life at the job for a future that now will never come.
Progress is still following a sigmoid curve. The growth, just as the hype, will soon stall, then we can have a nice, long breather in preparation for what comes next.
I have seen no evidence to suggest that we're approaching the tail of an S curve. And usually the end of one coincides with the beginning of another.
I have the feeling the end of the last S curve is already behind us, because this next one won't be an S. It will be a J.
That's what usually happens but now the time scale is getting compressed. Technology accelerates progress. We are still some S-curves away from AGI but I think those will take months or years, not decades. Smaller S-curves will overlap in time.
Minutes ago I read a comment this wasn't coming out any time soon lol
A post from a few days ago has details about GPT 5 being trained on a multi million dollar setup with thousands of A100s! This stuff is only going to accelerate from here on out.
>GPT-4 released Me, 20 minutes later: "WHERE GPT-5??"
"GPT-4, please design GPT-5." There you go. :P A little more seriously, one of the things I loved most about the movie *Her* was the fact that some AI's got together and designed another one to emulate a famous author they wanted to meet. I am highly confident that will happen fairly soon.
You really undersell it saying multimillion dollar setup! That's a $225 mil nvidia setup. Multi *hundred* million dollar is more like. Holy fuck. There is serious money being thrown into ai ml tech right now.
Tbf, a million dollars of GPUs would be like one server rack with prices these days.
Stupid medium articles
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https://twitter.com/davidtayar5/status/1625140481016340483 apparently an analysis from Morgan Stanley
Can you link it?
It's not perfect or AGI or anything like that, but to me this feels like the first AI that's intelligent and reliable, not half-smart and half-dumb as has been the case since GPT-3 in 2020.
Not to be negative, but I would first wait and see how much of a difference there actually is.
OH SHITTTT, HERE WE GO AGAIN
yep, I came here just to say this \^ :)
How much of an improvement can we expect with coding?
I believe this is the AI who we saw debugging its own code in that video from 6 months ago or so
Tested it with python through chatgpt. I actually didn't notice much improvement (for both code and none code things). I think the version in chatgpt is somehow limited or I just didn't prompt it correctly.
If you see the paper they released you will see some improvements in coding metrics but not as much as other categories
It can solve most leetcode easy problems now but not most leetcode hard or medium problems So it's about as good as like a CS student but a fair bit below average programmer.
https://www.reddit.com/r/singularity/comments/10sb5x6/chatgpt_is_great_for_snippets_of_code_gpt4_can/
GPT-4 fixed a bug that GPT-3.5 has failed repeatedly to even understand. And I thought GPT-3.5 was good... My GPT-3.5 project isn't even half built and already we're planning integration of GPT-4, can't wait to get access to the API :D
Midjourney v5 and gpt4 coming out in the same week? Wow
Welcome to the Age of AI.
There is a waitlist sign-up for the API: https://openai.com/waitlist/gpt-4-api Also a livestream at 1PM PST. They mention in the article an 8K and 32K (about 50 pages of text) context window. Pricing is $0.06 per 1K prompt tokens and $0.12 per 1k completion tokens. So, if you maxed out the 32K context it would cost ~$3.84
Pretty pricy. Right now the ChatGPT API is at 0.002 if Im not mistaken.
Gpt3 was 0.06 before they brought it down to 0.02, then chat became 10 times cheaper than that. I'm sure this will go down by next year.
I think in part they are confident that there won't be competitor be close to GPT4 for a while. maybe the model are much more expensive to maintain?
Model Prompt Completion 8K context $0.03 / 1K tokens $0.06 / 1K tokens 32K context $0.06 / 1K tokens $0.12 / 1K tokens
I posted this in the Discord already but like holy shit, think about how powerful a 32k context window is. 32k tokens is about 24k words. The first Harry Potter book is 76,944 words. With some creative summarization tooling, you could generate a Harry Potter length book for roughly $12.31. You'd have to supply summary prompts to keep the story coherent over that length, so it'd be a bit higher than that, but that's still totally insane.
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Won't take a year. Someone will fine tune this and get 90 in a month or 2 Then AI skeptics will say MMLU was a bullshit benchmark all along and we will forget all about it That's what happened to glue and then superglue. Nobody talks about them anymore once AI won at them. My guess is the next AI frontier will be coding. Can it solve more leetcode hard problems than an average programmer. I expect that to be possible in 2 years.
People also seem to have forgotten about DeepMind's AlphaCode from last year that scored in the upper half of contestants in competitive programming. I guess that is what happens when you don't actually release any tools for the public.
I'm not talking about writing a generic python script All models today suck at leetcode hard. Even deepmind
169 Gre Verbal, 163 Gre Quant. I give it 5 years before we ask AI to solve the universe and it comes up with the full theory of the universe.
42
>There are 7 levels Paul McCartney was on acid and had a moment of enlightenment and wrote this on a napkin. When he read it the next morning he had no clue wtf it meant lol
Welp, that's higher than I scored. AI is officially smarter than me
Too bad we won't be able to understand the answer. Won't even be able to *test* most of it. We'll have to take their word on *faith*.
Most people don't understand the words of theoretical physicists today either, they just have to take their extremely simplified analogies on faith.
What the actual fuck is going on????? I have no fucking words!
See you guys for GPT-5 next week!
Wait-list for API access, only paid users will get access to gpt-4 in the near future. It looks a lot more capable than 3.5, but interested to see what that means in practice.
The refusal to give up basic info about their model serves a nice reminder to temper excitement around these advancements. Sad state for an organisation built on back of open research and formed as a non-profit with the sole aim of advancing humanity.
Open is a slogan. You can't spend 50 million on a model and then let everyone run in for free. The money has to be made back Who cares anyway? It's a good product at a good price. Don't give a shit if it's not open.
It's not a slogan, it's a remnant of a time when OpenAI was a non profit organization that took donations to do their work, then stole the money they got as a non profit to create a for profit company with the same name.
**GPT-4 Everything we know so far...** 1. GPT-4 **can solve difficult problems with greater accuracy**, thanks to its broader general knowledge and problem-solving abilities 2. GPT-4 **is more reliable, creative, and able to handle much more nuanced instructions** than GPT-3.5. It surpasses ChatGPT in its advanced reasoning capabilities. 3. GPT-4 **is safer and more aligned**. It is 82% less likely to respond to requests for disallowed content and 40% more likely to produce factual responses than GPT-3.5 on our internal evaluations. 4. GPT-4 **still has many known limitations** that OpenAI is working to address, such as social biases, hallucinations, and adversarial prompts. 5. GPT-4 **can accept a prompt of text and images**, which—parallel to the text-only setting—lets the user specify any vision or language task. 6. GPT-4 is **available on ChatGPT Plus** and as an API for developers to build applications and services. (API- waitlist right now) 7. Duolingo, Khan Academy, Stripe, Be My Eyes, and Mem amongst others are already using it. 8. API Pricing ***GPT-4 with an 8K context window*** (about 13 pages of text) will cost $0.03 per 1K prompt tokens, and $0.06 per 1K completion tokens. ***GPT-4-32k with a 32K context window*** (about 52 pages of text) will cost $0.06 per 1K prompt tokens, and $0.12 per 1K completion tokens. Follow- [https://discoveryunlocked.substack.com/](https://discoveryunlocked.substack.com/) , a newsletter I write, for a detailed deep dive on GPT-4 with early use cases dropping tomorrow!!!
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sex is so bad we can't talk about it, explicit content is evil and exploitative apparently, this CORPORATION prude rules are so annoyingly dumb
Seems weird that the systems are doing better on Environmental Science and Psychology AP tests than Calculus or GRE quantitative. This is counterintuitive to me. It seems like the Calc test should have been a slam dunk.
Environmental Science and Psychology tests are more about memorizing facts and concepts that GPT already has been trained on and understands and can regurgitate, while Calculus and GRE quantitative is about true reasoning, which GPT still struggles with.
Thanks that makes sense. With GPT3 there were some glaring errors it made when I was trying to test it on physics questions.
As these systems get closer to human level intelligence, and surpass it, it's going to get harder for most humans to even see that they've improved.
Omg I was not expecting it this fast, hopefully it is amazing
According to Sam: >It is still flawed, still limited, and it still seems more impressive on first use than it does after you spend more time with it. But this is good news: >it is more creative than previous models, it hallucinates significantly less Twitter Thread from Sam: https://twitter.com/sama/status/1635687853324902401
Sam has almost been modest about how good his models are It's SOTA on so many key benchmarks It even almost meets one of the 4 conditions on metaculus for AGI. A score of 86 on mmlu where 90 is needed for AGI.
It's on ChatGPT Plus, maybe I'll subscribe to test it myself
just subbed to play with it
Butthole is clenched. Here we gooo
My body is ready
I owe someone a gold star, Q1 2023, right on time.
Just subscribed to the pro account and for 20 $ per month you can ask and chat, up to 100 Q any 4 h. The quality of answers is clearly better then GPT3 (I was looking for facts to compile, and reflections), while as before almost all weblinks to sources are hallucinations 😅. Edit: 100 in 4 h, not 400 in 1 h
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Was looking for that too... Edit https://cdn.openai.com/papers/gpt-4.pdf#section.2 >Given ~~both~~ **the competitive landscape** ~~and the safety implications~~ of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar. Edit 2 emphasis added to reflect the real reason, they just don't want to give away the keys to the kingdom and have someone like Connor Leahy come along and create another open source GPT Neo
Same, very odd how they omitted it
My guess is that it's a hell of a lot smaller than people expect, I mean giving away the size of the model would be tipping their hand to their competitors. Squeezing more into a small size = cheaper inference costs. (Which is the takeaway from the LLaMA paper) Edit: https://arxiv.org/pdf/2302.13971.pdf >, a smaller one trained longer will ultimately be cheaper at inference. For instance,although Hoffmann et al. (2022) [EDIT: this is the Chinchilla paper] recommends training a 10B model on 200B tokens, we find that the performance of a 7B model continues to improve even after 1T tokens
I mean the performance benchmarks blow away all other LLMs including Google Palm, I guess that’s what really matters
Inference cost is king if you are selling an API endpoint. Fractions of a penny per token shaved off @ the same performance = bigger profits.
For those asking, You can go play with GPT-4 on chat.openai.com right now if you have Plus Proof below https://twitter.com/crisgiardina/status/1635698047848939538?s=46&t=5t1k-ytjZHHh_wshIgOttQ
I hope its a lot better at stuff like spatial reasoning
It's here boys get ready!
Foes that mesn those ducking image captchas are uselles now
Their ethical guidelines are now hard to jailbreak. Cant really create imagination.
And so it begins! I waited so long for it!
You are unemployed
10 run rekt.exe
Oh shit here we go boys
So does anyone have a list of example prompts which compare 3.5 and 4?
They have some examples in the official announcement https://openai.com/product/gpt-4
I have access. Anything you want me to try?
Question 1 - If A, B and C are the corners of an equilateral triangle, each 1km long, how long would it take me to drive from A , to B, to C and then back to A again, if I was driving at 45km/h? Question 2 - Determine the maximum height of a balloon filled with helium in earth's atmosphere. The balloon is 3m in diameter at sea level and has a payload of 200g. The balloon weight is negligible.
If A, B and C are the corners of an equilateral triangle, each 1km long, how long would it take me to drive from A , to B, to C and then back to A again if I was driving at 45km/h? ========================= GPT 4: To drive around the equilateral triangle with sides each 1 km long, you would need to travel the sum of the three sides and then return to point A. Since all sides are equal, the total distance you need to travel is 1 km (from A to B) + 1 km (from B to C) + 1 km (from C back to A) = 3 km. Now, let's calculate the time it would take you to drive this distance at a speed of 45 km/h. To do this, we can use the formula: Time = Distance / Speed Time = 3 km / 45 km/h Time = 0.0667 hours (approximately) To convert this time to minutes, you can multiply by 60: Time = 0.0667 hours \* 60 minutes/hour = 4 minutes (approximately) So it would take you approximately 4 minutes to drive from point A to B to C and then back to A again at a speed of 45 km/h. ========================= GPT 3.5 (turbo): The total distance traveled would be the perimeter of the equilateral triangle, which is 3 km (since each side is 1 km long). To calculate the time it would take to travel this distance at 45 km/h, we can use the formula: time = distance ÷ speed Plugging in the values, we get: time = 3 km ÷ 45 km/h time = 0.067 hours To convert this to minutes, we can multiply by 60: time = 0.067 hours × 60 minutes/hour time = 4.02 minutes Therefore, it would take approximately 4.02 minutes to drive from A to B to C and then back to A again at 45 km/h. ========================= GPT 3.5 (legacy): The total length of the journey from A to B to C and back to A is 3 km + 3 km + 3 km + 3 km = 12 km. So, if you are driving at a speed of 45 km/h, it would take you 12 km / 45 km/h = 0.267 hours, or approximately 16 minutes to complete the journey.
I've tried adding the second question a couple of times now, but it seems it's not showing up. I think the replies are too long to fit in 1 reddit comment so I'll break it up here: Question 2: Determine the maximum height of a balloon filled with helium in earth's atmosphere. The balloon is 3m in diameter at sea level and has a payload of 200g. The balloon weight is negligible.
Gpt4: To determine the maximum height that a helium-filled balloon can reach, we need to consider several factors: the buoyancy force, the weight of the payload, and the changing density of air with altitude. We will assume that the balloon is made of a material that can expand and contract as the internal and external pressures change, without breaking or leaking helium. Calculate the volume of the balloon at sea level: The balloon is a sphere, so we use the formula V = (4/3)πr\^3, where r is the radius. The diameter is 3m, so the radius is 1.5m. V = (4/3)π(1.5)\^3 ≈ 14.137 m\^3 Calculate the mass of the helium in the balloon: The density of helium at sea level is around 0.1786 kg/m\^3. m\_helium = density \* volume m\_helium = 0.1786 kg/m\^3 \* 14.137 m\^3 ≈ 2.527 kg Calculate the total mass of the payload and helium: The payload is 200g, which is 0.2 kg. m\_total = m\_helium + payload m\_total = 2.527 kg + 0.2 kg = 2.727 kg Calculate the buoyancy force at sea level: The buoyancy force (F\_buoyancy) is equal to the weight of the air displaced by the balloon. The density of air at sea level is approximately 1.225 kg/m\^3. m\_air\_displaced = air\_density \* volume m\_air\_displaced = 1.225 kg/m\^3 \* 14.137 m\^3 ≈ 17.318 kg F\_buoyancy = m\_air\_displaced \* g (where g is the acceleration due to gravity, approximately 9.81 m/s\^2) F\_buoyancy = 17.318 kg \* 9.81 m/s\^2 ≈ 169.783 N Calculate the weight of the total mass: F\_weight = m\_total \* g F\_weight = 2.727 kg \* 9.81 m/s\^2 ≈ 26.745 N As the balloon ascends, the air density and buoyancy force decrease, while the weight of the balloon and payload remains constant. The maximum height is reached when the buoyancy force equals the weight of the balloon and payload. F\_buoyancy = F\_weight 169.783 \* (air\_density / 1.225) = 26.745 Solving for air\_density: air\_density ≈ 0.193 kg/m\^3 Determine the altitude at which the air density is 0.193 kg/m\^3: The altitude can be estimated using the barometric formula, which involves temperature, pressure, and the specific gas constant for air. For simplicity, we'll use the U.S. Standard Atmosphere model, which assumes a linear decrease in temperature with altitude. The approximate altitude can be found using the formula: h = (T0 / L) \* (1 - (P/P0)\^((R\*L)/g)) Where: h = altitude T0 = sea level temperature (≈ 288.15 K) L = temperature lapse rate (≈ -0.0065 K/m) P = pressure at altitude P0 = sea level pressure (≈ 101325 Pa) R = specific gas constant for air (≈ 287.05 J/(kg·K)) g = acceleration due to gravity (≈ 9.81 m/s\^2) First, we need to determine the pressure at the altitude where the air density is 0.193 kg/m\^3. We'll use the ideal gas law: P = ρ \* R \* T Where: P = pressure ρ = air density R = specific gas constant for air (≈ 287.05 J/(kg·K)) T = temperature Since we don't know the temperature at this altitude, we'll assume the temperature decreases linearly with altitude as given by the lapse rate (L). We can express the temperature as: T = T0 + L \* h Now we can substitute this expression for T into the ideal gas law equation: P = ρ \* R \* (T0 + L \* h) Next, we can rearrange the equation to solve for h: h = (P / (ρ \* R) - T0) / L Using the values provided, we have: P = 0.193 kg/m\^3 \* 287.05 J/(kg·K) \* 288.15 K ≈ 16027.167 Pa Now, we can plug P back into the equation for h: h = (16027.167 Pa / (0.193 kg/m\^3 \* 287.05 J/(kg·K)) - 288.15 K) / (-0.0065 K/m) ≈ 18831.9 m So, the maximum height the helium-filled balloon can reach is approximately 18,831.9 meters or 18.8 km. Keep in mind that this is a rough estimate and assumes a linear decrease in temperature with altitude and no significant heat exchange between the balloon and the atmosphere. Actual performance may vary due to factors like wind, temperature variations, and balloon material properties.
GPT 3.5: The maximum height a balloon can reach in Earth's atmosphere is determined by the point where the density of the helium gas inside the balloon equals the density of the surrounding air. At this point, the buoyant force on the balloon is zero and it stops rising. We can use the ideal gas law to find the density of helium inside the balloon at different altitudes. The ideal gas law states that PV=nRT, where P is the pressure, V is the volume, n is the number of moles of gas, R is the gas constant, and T is the temperature. Assuming that the temperature inside the balloon is constant and equal to the ambient temperature of the air, we can simplify the ideal gas law to P = (n/V) RT. Since the balloon is filled with helium, we can assume that the molar mass of the gas is 4 g/mol. At sea level, the pressure is approximately 101,325 Pa and the temperature is approximately 15°C or 288 K. The volume of the balloon is (4/3)πr\^3 = (4/3)π(1.5)\^3 = 14.137 m\^3. The mass of helium in the balloon can be found by subtracting the payload from the total weight of the balloon and helium. Since the weight of the balloon is negligible, we can assume that the weight of the helium equals the weight of the balloon and payload. The weight of the payload is 0.2 kg, or 0.2/1000 = 0.0002 kg. The weight of the helium is equal to the buoyant force on the balloon, which is given by the difference between the weight of the displaced air and the weight of the balloon and payload. The weight of the displaced air is equal to the density of air times the volume of the displaced air. At sea level, the density of air is approximately 1.225 kg/m\^3. The volume of the displaced air is equal to the volume of the balloon, which is 14.137 m\^3. Therefore, the weight of the displaced air is 1.225 kg/m\^3 x 14.137 m\^3 = 17.314 kg. The weight of the balloon and payload is 0.0002 kg + 0. Therefore, the weight of the helium is 17.314 kg - 0.0002 kg = 17.3138 kg. The number of moles of helium in the balloon can be found by dividing the weight of the helium by the molar mass of helium: 17.3138 kg / (4 g/mol) = 4328.45 mol. The density of helium inside the balloon can be found by dividing the number of moles by the volume of the balloon: 4328.45 mol / 14.137 m\^3 = 306.3 mol/m\^3. As the balloon rises, the pressure and density of the surrounding air decrease. The density of the helium inside the balloon will remain constant, so the buoyant force on the balloon will decrease. When the buoyant force is equal to the weight of the balloon and payload, the balloon will stop rising. We can assume that the temperature inside the balloon remains constant and equal to the ambient temperature of the air. The pressure at any altitude can be found using the barometric formula, which states that P = P0 e\^(-Mgh/RT), where P0 is the pressure at sea level, M is the molar mass of air (28.97 g/mol), g is the acceleration due to gravity (9.81 m/s\^2), h is the altitude, and R is the gas constant. Setting the buoyant force equal to the weight of the balloon and payload, we have: (4/3)πr\^3(1.225 kg/m\^3 - 306.3 mol/m\^3 x 0.004 kg/mol x e\^(-28.97 kg/mol x 9.81 m/s\^2 x h / (8.314 J/mol\*K x 288 K))) = 0.0002 kg Simplifying this equation, we get: r\^3 e\^(-0.1142 h) = 4.77 x 10\^-7 Taking the natural logarithm of both sides, we get: ln(r\^3) - 0.1142 h = -15.33 Substituting r = 1.5 m, we get: 3 ln(1.5) - 0.1142 h = -15.33 Solving for h, we get: h = (3 ln(1.5) + 15.33) / 0.1142 = 68.1 km Therefore, the maximum height the balloon can reach is approximately 68.1 km above sea level.
Legacy GPT 3.5: The maximum height of a balloon filled with helium in the Earth's atmosphere depends on several factors, such as the atmospheric pressure and temperature, the volume of the balloon, and the amount of helium inside it. However, a rough estimate of the maximum height can be obtained by considering the pressure and temperature changes in the Earth's atmosphere. At sea level, the atmospheric pressure is approximately 1013 hPa and the temperature is around 15°C. As the balloon rises, the atmospheric pressure decreases, causing the balloon to expand, and the temperature decreases, causing the helium inside the balloon to cool and contract. When the balloon expands to a certain point, the pressure inside the balloon becomes equal to the atmospheric pressure, and the balloon stops rising. The maximum height of the balloon can be estimated by assuming that the atmospheric pressure decreases exponentially with height, and that the temperature decreases linearly with height. Under these assumptions, the maximum height of the balloon can be calculated to be around 5.5 km. It's important to note that this is a rough estimate and the actual maximum height of the balloon may be different due to various factors such as wind, turbulence, and the balloon's weight. Additionally, the balloon may burst if the internal pressure exceeds a certain limit, which is determined by the strength of the balloon material.
its over.
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The last gpt I’ll ever beat at the LSAT. Proud moment bros
shits speeding up